Detect chromosomal duplications

Setup

Libraries

library(tidyverse)
library(ggtree)
library(ggtreeExtra)
library(ape)
library(ggnewscale)
library(RColorBrewer)
library(svglite)
source("scripts/metadata_colors.R")

Paths

metadata_path <- 
    "data/processed/metadata_ashton_desj_all_weavepop_H99.csv"
ploidy_path <- 
    "results/tables/ploidy_from_plots.tsv"
duplications_path <- 
    "results/tables/duplications.tsv"
merged_tree_path <- 
    "data/processed/tree_merged.newick"
tree_merged_duplications_path <- 
    "results/trees_dups/tree_merged_duplications.svg"
tree_merged_duplications_only_duplicated <-  
    "results/trees_dups/tree_merged_duplications_only_duplicated.svg"

Metadata

Load the necessary data

metadata <- read.csv(
    metadata_path,
    header = TRUE)%>%
    select(strain, everything())

Get one dataframe for each variable to be plotted as a separate metadata column in the tree

metadata$vni_subdivision <- factor(metadata$vni_subdivision,
                            levels = c("VNIa-4", "VNIa-5", "VNIa-32", 
                            "VNIa-93", "VNIa-X", "VNIa-Y", "VNIb", 
                            "VNIc", "VNIa-outlier"))
metadata$country_of_origin <- factor(metadata$country_of_origin,
                                levels = names(country_colors))

sublineage <- metadata %>%
                filter(lineage == "VNI")%>%
                select(strain, vni_subdivision)%>%
                column_to_rownames("strain")%>%
                droplevels()
lineage <- metadata %>%
            select(strain, lineage)%>%
            column_to_rownames("strain")
dataset <- metadata %>%
            select(strain, dataset)%>%
            column_to_rownames("strain")
source <- metadata %>%
            select(strain, source)%>%
            column_to_rownames("strain")
country <- metadata %>%
            select(strain, country_of_origin)%>%
            column_to_rownames("strain")     

ploidy <- read.delim(
    ploidy_path,
    header=TRUE,
    sep="\t")%>%
    select(strain, ploidy)%>%
    filter(ploidy != "haploid")%>%
    distinct()%>%
    column_to_rownames("strain")

Duplications

duplications <- read.delim(
    duplications_path,
    sep = "\t", header = TRUE, stringsAsFactors = TRUE)

duplications_full <- duplications %>%
    select(strain, chromosome) %>%
    distinct()

Make matrix of duplicated chromosomes

dup_chroms <- duplications_full %>%
    select(strain, chromosome)%>%
    mutate(duplicated_full = 1)%>%
    arrange(chromosome)%>%
    pivot_wider(names_from = chromosome, values_from = duplicated_full, values_fill = 0)%>%
    column_to_rownames("strain")%>%
    mutate(across(everything(), ~ ifelse(. == 1, cur_column(),"Euploid")))

euploid_strain <- metadata %>%
    filter(!strain %in% duplications_full$strain)%>%
    select(strain)

for (chrom in colnames(dup_chroms)){
    euploid_strain[chrom] <- "Euploid"
}

dup_chroms <- euploid_strain %>%
    column_to_rownames("strain") %>%
    bind_rows(dup_chroms)

Tree

tree <- read.tree(merged_tree_path)

Remove tips that are not in metadata$strain

tree <- drop.tip(tree, setdiff(tree$tip.label, metadata$strain))

Tree info

Get the node number of the Most Recent Common Ancestor of each lineage

VNI_node <- getMRCA(tree, c("Tu241-1","UI_31647-2"))
VNII_node <- getMRCA(tree, c("C2","C12"))
VNBI_node <- getMRCA(tree, c("Tu229-1","Ftc267-2"))
VNBII_node <- getMRCA(tree, c("MW-RSA3321","MW-RSA3179"))

nodes_lineages <- data.frame(
    lineage = c("VNI", "VNII", "VNBI", "VNBII"),
    mrca = c(VNI_node, VNII_node, VNBI_node, VNBII_node)
)

VNIa4_node <- getMRCA(tree, c("04CN-30-008","UI_31647-2"))
VNIa5_node <- getMRCA(tree, c("BMD852","14936_1#45"))
VNIa93_node <- getMRCA(tree, c("04CN-65-080","04CN-65-002"))
VNIa32_node <- getMRCA(tree, c("BMD942","BMD2801"))
VNIaX_node <- getMRCA(tree, c("Bt48","04CN-63-007"))
VNIaY_node <- getMRCA(tree, c("04CN-65-073","Bt138"))
VNIb_node <- getMRCA(tree, c("04CN-65-096","MW-RSA722"))
VNIc_node <- getMRCA(tree, c("Bt20","Bt11"))

nodes_vnisublineages <- data.frame(
    sublineage = c(
                "VNIa-4", "VNIa-5", "VNIa-93",
                "VNIa-32", "VNIa-X", "VNIa-Y",
                "VNIb", "VNIc"),
    mrca = c(
            VNIa4_node, VNIa5_node, VNIa93_node,
            VNIa32_node, VNIaX_node, VNIaY_node,
            VNIb_node, VNIc_node))

nodes_sublineages <- data.frame(
    sublineage = c("VNI", "VNII", "VNBI", "VNBII",
                "VNIa-4", "VNIa-5", "VNIa-93",
                "VNIa-32", "VNIa-X", "VNIa-Y",
                "VNIb", "VNIc"),
    mrca = c(VNI_node, VNII_node, VNBI_node, VNBII_node,
            VNIa4_node, VNIa5_node, VNIa93_node,
            VNIa32_node, VNIaX_node, VNIaY_node,
            VNIb_node, VNIc_node))

Plots

chrom_colors <- brewer.pal(7, "Paired")
names(chrom_colors) <- c("chr01", "chr04",
                         "chr06", "chr09", 
                         "chr12","chr13", "chr14")
chrom_dup_colors <- c(chrom_colors, "Euploid" = "grey93")

Country, source, duplications in one ring per chromosome

m <- ggtree(tree, 
        ladderize = TRUE,
        layout = "circular", 
        branch.length = "none",
        size = 0.1) %<+%  metadata +
    geom_tiplab(color = "black", size = 0.5, offset = 0.01)+
    geom_text(aes(label = nodes_lineages$lineage[match(node, nodes_lineages$mrca)]), 
                        size = 2, , fontface = "bold",
                        hjust = 1.25, vjust = -0.5)+
    geom_hilight(data=nodes_vnisublineages, 
        aes(node=mrca, fill=sublineage), alpha = 0.8)+
        scale_fill_manual(name = "Sublineage", values = sublineage_shading)+
    guides(fill = FALSE)+
    new_scale_fill()+
    geom_tree(size = 0.1)+
    geom_tippoint(aes(color = country_of_origin),
                size = 0.3)+
    scale_color_manual(name = "Country", values = country_colors,
                        limits = levels(country$country_of_origin))+
    guides(color = guide_legend(override.aes = list(size = 5), order = 1, ncol = 2))

m1 <- gheatmap(m, source, width=.05, colnames=FALSE, offset=3) +
        scale_fill_manual(values = source_colors, name="Source", na.translate = FALSE)+
        guides(fill = guide_legend(order = 2))+
        new_scale_fill()
m2 <- gheatmap(m1, dup_chroms, width=.32, colnames = FALSE, offset=6) +
    scale_fill_manual(values = chrom_dup_colors, 
                    name="Duplicated\nchromosomes", 
                    na.translate = FALSE )+
    guides(fill = guide_legend(order = 5))+
        geom_cladelab(data = nodes_vnisublineages, 
                mapping = aes(node = mrca, label = sublineage),
                align = TRUE, face = "bold",
                angle = "auto", offset = 20)+
    theme(legend.position = "bottom",
    legend.direction = "vertical")
m2

Country, source, duplications in one ring per chromosome and ploidy

m2 <- gheatmap(m1, dup_chroms, width=.32, colnames = FALSE, offset=5,) +
    scale_fill_manual(values = chrom_dup_colors, 
                    name="Duplicated\nchromosomes", 
                    na.translate = FALSE )+
    guides(fill = guide_legend(order = 3))+
    new_scale_fill()
m3 <- gheatmap(m2, ploidy, width=.05, colnames=FALSE, offset=17) +
        scale_fill_brewer(palette = "Set1", 
             name="Ploidy", na.translate = FALSE)+
        guides(fill = guide_legend(order = 4))+
        new_scale_fill()+
        geom_cladelab(data = nodes_vnisublineages, 
                mapping = aes(node = mrca, label = sublineage),
                align = TRUE, face = "bold",
                angle = "auto", offset = 25)+
        theme(legend.position = "bottom",
        legend.direction = "vertical")
m3

ggsave(tree_merged_duplications_path, m3, height = 15, width = 15, units = "in", dpi = 900)

Warning: Removed 2107 rows containing missing values or values outside the scale range
(`geom_text()`).

Country, source and duplications in one ring

aneuploid <- duplications_full %>%
    group_by(strain)%>%
    summarise(chromosome = str_c(chromosome, collapse="_")) %>%
    column_to_rownames("strain")

md <- gheatmap(m1, aneuploid, width=.05, colnames = FALSE, offset=5.5) +
    scale_fill_brewer(name = "Duplicated\nchromosomes", palette = "Paired", na.value = "gray90")+
    guides(fill = guide_legend(order = 5))+
    geom_cladelab(data = nodes_vnisublineages, 
            mapping = aes(node = mrca, label = sublineage),
            align = TRUE, face = "bold",
            angle = "auto", offset = 7)
md

Country, source and duplications in one ring and ploidy

m3 <- gheatmap(m1, aneuploid, width=.05, colnames = FALSE, offset=5.5) +
    scale_fill_brewer(name = "Duplicated\nchromosomes", palette = "Paired", na.value = "gray90")+
    guides(fill = guide_legend(order = 5))+
    new_scale_fill()

m4 <- gheatmap(m3, ploidy, width=.05, colnames=FALSE, offset=8) +
        scale_fill_brewer(palette = "Set1", 
             name="Ploidy", na.translate = FALSE)+
        guides(fill = guide_legend(order = 4))+
        new_scale_fill()+
        geom_cladelab(data = nodes_vnisublineages, 
                mapping = aes(node = mrca, label = sublineage),
                align = TRUE, face = "bold",
                angle = "auto", offset = 10)+
        theme(legend.position = "bottom",
        legend.direction = "vertical")
m4

ggsave(tree_merged_duplications_path, m2, height = 15, width = 15, units = "in", dpi = 900)

Warning: Removed 2107 rows containing missing values or values outside the scale range
(`geom_text()`).

Dataset, country, source, duplications in one ring per chromosome

m <- ggtree(tree, 
        ladderize = TRUE,
        layout = "circular", 
        branch.length = "none",
        size = 0.1) %<+%  metadata +
    geom_tiplab(color = "black", size = 0.5, offset = 0.01)+
    geom_text(aes(label = nodes_lineages$lineage[match(node, nodes_lineages$mrca)]), 
                        size = 2, , fontface = "bold",
                        hjust = 1.25, vjust = -0.5)+
    geom_hilight(data=nodes_vnisublineages, 
        aes(node=mrca, fill=sublineage), alpha = 0.8)+
        scale_fill_manual(name = "Sublineage", values = sublineage_shading)+
    guides(fill = FALSE)+
    new_scale_fill()+
    geom_tree(size = 0.1)+
    geom_tippoint(aes(color = dataset), size = 0.3)+
    scale_color_manual(name = "Dataset", values = dataset_colors)+
    guides(color = guide_legend(override.aes = list(size = 5), order = 1))

m1 <- gheatmap(m, country, width=.05, colnames=FALSE, offset=3) +
        scale_fill_manual(values = country_colors, name="Country",
            na.translate = FALSE, limits = levels(country$country_of_origin))+
        guides(fill = guide_legend(order = 2, ncol = 2))+
        new_scale_fill()

m2 <- gheatmap(m1, source, width=.05, colnames=FALSE, offset=4) +
        scale_fill_manual(values = source_colors, name="Source", na.translate = FALSE)+
        guides(fill = guide_legend(order = 4))+
        new_scale_fill()
m3 <- gheatmap(m2, dup_chroms, width=.32, colnames = FALSE, offset=7) +
    scale_fill_manual(values = chrom_dup_colors, 
                    name="Duplicated\nchromosomes", 
                    na.translate = FALSE )+
    guides(fill = guide_legend(order = 5))+
        geom_cladelab(data = nodes_vnisublineages, 
                mapping = aes(node = mrca, label = sublineage),
                align = TRUE, face = "bold",
                angle = "auto", offset = 21)+
    theme(legend.position = "bottom",
    legend.direction = "vertical")
m3

Tree with only the samples that have duplications and the references

keep_strains <- c(levels(duplications_full$strain), "H99", "Bt22", "Bt89")
tree_dups <- drop.tip(tree, setdiff(tree$tip.label, keep_strains))
sublineage <- sublineage %>%
                filter(rownames(.) %in% keep_strains)%>%
                droplevels()

Tree info

Get the node number of the Most Recent Common Ancestor of each lineage

VNI_node <- getMRCA(tree_dups, c("Bt139","H99"))
VNII_node <- getMRCA(tree_dups, c("8-1","C12"))
VNBI_node <- getMRCA(tree_dups, c("Bt22","NRHc5045.ENR.CLIN.ISO"))
VNBII_node <- getMRCA(tree_dups, c("Bt109","Bt89"))

nodes_lineages <- data.frame(
    lineage = c("VNI", "VNII", "VNBI", "VNBII"),
    mrca = c(VNI_node, VNII_node, VNBI_node, VNBII_node)
)

VNIa4_node <- getMRCA(tree_dups, c("20427_3#26","20427_4#13"))
VNIa5_node <- getMRCA(tree_dups, c("Bt139","Bt141"))
VNIa93_node <- getMRCA(tree_dups, c("04CN-64-024","04CN-64-011"))
VNIa32_node <- getMRCA(tree_dups, c("04CN-65-072","In2632"))
VNIb_node <- getMRCA(tree_dups, c("H99","MW-RSA6134"))
VNIc_node <- getMRCA(tree_dups, c("LP-RSA3042","PMHc1031A.ENR.INI.LP"))

nodes_vnisublineages <- data.frame(
    sublineage = c(
                "VNIa-4", "VNIa-5", "VNIa-93",
                "VNIa-32", 
                "VNIb", "VNIc"),
    mrca = c(
            VNIa4_node, VNIa5_node, VNIa93_node,
            VNIa32_node,
            VNIb_node, VNIc_node))

nodes_sublineages <- data.frame(
    sublineage = c("VNI", "VNII", "VNBI",# "VNBII",
                "VNIa-4", "VNIa-5", "VNIa-93",
                "VNIa-32", "VNIa-X", "VNIa-Y",
                "VNIb", "VNIc"),
    mrca = c(VNI_node, VNII_node, VNBI_node, #VNBII_node,
            VNIa4_node, VNIa5_node, VNIa93_node,
            VNIa32_node, VNIaX_node, VNIaY_node,
            VNIb_node, VNIc_node))

m <- ggtree(tree_dups, 
        ladderize = TRUE,
        layout = "rectangular", 
        branch.length = "none",
        size = 0.1) %<+%  metadata +
    geom_tiplab(color = "black", size = 4, offset = 0.1)+
    geom_text(aes(label = nodes_lineages$lineage[match(node, nodes_lineages$mrca)]), 
                        size = 2, , fontface = "bold",
                        hjust = 1.25, vjust = -0.5)+
    geom_hilight(data=nodes_vnisublineages, 
        aes(node=mrca, fill=sublineage), alpha = 0.8)+
        scale_fill_manual(name = "Sublineage", values = sublineage_shading)+
    guides(fill = FALSE)+
    new_scale_fill()+
    geom_tree(size = 0.1)+
    geom_tippoint(aes(color = dataset), size = 3)+
    scale_color_manual(name = "Dataset", values = dataset_colors)+
    guides(color = guide_legend(override.aes = list(size = 5), order = 1))

m1 <- gheatmap(m, country, width=.03, colnames=FALSE, offset=2) +
        scale_fill_manual(values = country_colors, name="Country",
            na.translate = FALSE, limits = levels(country$country_of_origin))+
        guides(fill = guide_legend(order = 2, ncol = 2))+
        new_scale_fill()

m2 <- gheatmap(m1, source, width=.03, colnames=FALSE, offset=2.5) +
        scale_fill_manual(values = source_colors, name="Source", na.translate = FALSE)+
        guides(fill = guide_legend(order = 4))+
        new_scale_fill()
m3 <- gheatmap(m2, dup_chroms, width=.25, colnames = FALSE, offset=3) +
    scale_fill_manual(values = chrom_dup_colors, 
                    name="Duplicated\nchromosomes", 
                    na.translate = FALSE )+
    guides(fill = guide_legend(order = 5))+
        geom_cladelab(data = nodes_vnisublineages, 
                mapping = aes(node = mrca, label = sublineage),
                align = TRUE, face = "bold",
                angle = 0, offset = 6)+
    theme(legend.position = "bottom",
    legend.direction = "vertical")
m3

Dataset, lineage, sublineage, source, duplications

Lineage, sublineage, duplications

Lineage, duplications, sublineage

Lineage, duplications

ggsave(tree_merged_duplications_only_duplicated, m3, height = 8, width = 13, units = "in", dpi = 900)

Warning: Removed 73 rows containing missing values or values outside the scale range
(`geom_text()`).